Course Details
Course Details
What You'll Learn
Topic 1: Introduction to AI and Agentic AI for Finance
Topic 2: AI Agents for Financial Data and Analysis
Topic 3: Agentic Workflows for Financial Planning and Reporting
Topic 4: Risk, Compliance and Deploying Finance AI Agents
Course Info
Minimum Entry Requirement
Knowledge and Skills
- Able to operate using computer functions
- Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
- Positive Learning Attitude
- Enthusiastic Learner
Experience
- Minimum of 1 year of working experience.
This is an intermediate level course. The following prerequisite is assumed
Target Age Group: 18-65 years old
Minimum Software/Hardware Requirement
Software:
You will need the following for this course:
- Python 3 – free
- Visual Studio Code – free
- Google Colab – free, runs in the browser with a Google account
Hardware: Windows PC or Mac laptop
Job Roles
Job Roles
- Aspiring Software Developer
- Data Analyst
- Web Developer
- Automation Engineer
- Data Scientist
- System Administrator
- Bioinformatics Specialist
- Research Scientist
- Finance Professional
- Machine Learning Enthusiast
- GIS (Geographic Information System) Specialist
- IT Consultant
- Network Engineer
- Database Administrator
- Tech Entrepreneur.
Trainers
Trainers
Agents that read numbers, reason about them and prepare reports sit at the centre of Dr. Alfred Ang's recent work. Dr. Ang is a full-stack AI developer, Agentic AI solution architect and corporate trainer, and serves as Chief Technology Officer of Tertiary Infotech Academy Pte Ltd, the Singapore training organisation behind Tertiary Courses. Building end to end, from front-end screens and back-end services to databases, cloud deployment and native mobile apps, Dr. Ang has produced several finance-related systems. An HR and accounting platform built in Next.js runs leave accrual, attendance, payroll with payslips and expense claims for the academy, with native iPhone and Android apps for approvals on the go. An ERP prototype on Next.js and Postgres routes purchase orders through human-in-the-loop approvals by email, Asana or Telegram and three-way matches invoices against orders and receipts. A stock analysis dashboard pairs live market charts with an n8n Telegram AI agent that gives Buy, Sell or Hold views, while an investment advisor chatbot answers enquiries through n8n workflows. Dr. Ang also built an inventory forecasting agent that runs on a local language model through Ollama, flags items under reorder thresholds and computes forecasts, and a travel expense tracker app that converts more than 30 currencies using live exchange rates. Together with the rest of a portfolio of more than 300 public repositories on GitHub, these projects show agentic AI applied to real financial workflows with proper controls. Each one keeps a person firmly in charge of the final decision.
AI for Finance reflects that experience of putting agents to work on financial data while keeping people accountable for the result. Dr. Ang begins with an introduction to AI and agentic AI for finance, explaining how agents plan, reason, use tools and act, and how that differs from simply asking a chatbot a question. The second topic applies AI agents to financial data and analysis: extracting figures from statements and invoices, reconciling records, analysing ratios and explaining variances in plain language. Learners then build agentic workflows for financial planning and reporting, such as preparing budget forecasts, generating cash-flow scenarios and drafting management commentary that a finance lead can review and approve. The final topic covers risk, compliance and deploying finance AI agents responsibly, including audit trails, data privacy, access controls, model errors and the approval checkpoints Dr. Ang builds into ERP and accounting systems. Teaching is practical and example-driven; every concept is demonstrated with realistic sample data, and learners complete exercises that mirror day-to-day tasks in accounting, financial planning and analysis, and treasury. Dr. Ang encourages learners to bring their own reporting pain points so the class can explore which parts suit automation and which should remain manual. Participants finish with working workflows, reusable prompts and a practical roadmap for introducing agentic AI in their finance team. Learners also discuss how to present AI-generated analysis to auditors and senior management. To see the finance agents and accounting tools behind this course, visit https://github.com/alfredang
Review
Customer Reviews (9)
- Worth every cent Review by Course Participant/Trainee
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I found the course extremely useful and relevant to my job. Highly recommend it to others. (Posted on 28/05/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Highly recommended Review by Course Participant/Trainee
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A very practical course. The trainer made a complex topic simple and enjoyable to learn. (Posted on 06/05/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Excellent course Review by Course Participant/Trainee
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Very informative and interactive. The small class size meant we got a lot of personal attention. (Posted on 19/03/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Exceeded my expectations Review by Course Participant/Trainee
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The training was very practical and hands-on. I could apply what I learned to my work immediately. (Posted on 18/05/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Good course materials Review by Course Participant/Trainee
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Excellent delivery and good balance between theory and practice. Learned a lot in a short time. (Posted on 17/05/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
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